Social Media Content Analyser

Abstract

Social media analytics is the process of collecting information from social media and analyzing patterns in the data which helps businesses to make effective conclusions. In this project, we are going to implement concepts of Machine Learning, NLP, BDA and Data Science. Analysis of social media data like followers, likes, comments etc from platforms like Facebook, Instagram, Twitter, Youtube, Whatsapp. The project will be a web application as well as a mobile application. The end users can be business users, influencers and personal users who want to enhance their profile.The features of the project will be post scheduling which is a system that will automate the process of posting on a particular date and time, Once the condition is time, once the condition is satisfied then automatically post will be posted using social media API. A campaign is a planned sequence of activities and processes which promote an individual product, service, or resources. Campaign generation will be done by asking various questions and by processing that data campaign data will be generated. According to the user's requirement, input data will be arranged and a series of posts will be generated. To understand consumer's satisfaction and the feedback it is important to understand what consumers are thinking about the company. Consumer's sentiments about the business posts will be detected using sentiment analysis of comments. In this module the response of consumers on a certain post will be analysed using NLP and sentiment analysis for that ml algorithms like SVM, Naive Bayes will be used to classify and generate the data. When we will deploy this software for consumers, as per commercial aspects it is important to show advertisements. In the application only that ads will be displayed which are useful to the consumer's business using NLP and Neural Networks. Clustering algorithms like k-means clustering will be used to cluster popular Hashtags according to input tags given by the consumer for the selected post. User registration will be done by filling a form and data will be stored in a database(firebase). The engagement, ROI, the reach of a post are some important parameters to analyze. The analysis of social media data will be done using classification techniques using machine learning models like K-means clustering, Neural Networks, python libraries like pandas.